Water Chemical Oxygen Demand Detection System Based on LASSO Algorithm

Abstract

With the increasingly serious water environment problems, water quality safety has attracted much attention from the society. At present, chemical oxygen demand (COD) is a common monitoring item in water quality monitoring. The purpose of this paper is to study the design of water chemical oxygen demand detection system based on LASSO algorithm. Design the development environment and usage of the whole system in general, and design and implement the display functions in detail. Finally, the monitoring data of the water quality chemical oxygen demand detection system is integrated, the pollutant attenuation is calculated, the pollutant attenuation model is established, and the pollutant attenuation value is calculated through the pollutant attenuation coefficient. From the water quality indicators, 10 available variables were screened for quantification, and the Lasso method was used to select the influencing factors. Finally, water temperature, pH, transparency, and electrical conductivity were determined. These four variables had the most significant impact on algal blooms.